Automatic performance management in component based software systems

Diaconescu, Ada; Mos, Adrian; Murphy, John

doi:10.1109/icac.2004.1301366

Cited by 30 publications

(21 citation statements)

References 11 publications

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“…Research on approaches to optimizing middleware at runtime has focused on choosing optimal component implementations from a set of available alternatives based on the current execution context [21]. QuO [22] is a dynamic QoS framework that allows dynamic adaptation of desired behavior specified in contracts, selected using proxy objects called delegates with inputs from runtime monitoring of resources by system condition objects.…”

Section: Discussionmentioning

confidence: 99%

Applying Model Transformations to Optimizing Real-Time QoS Configurations in DRE Systems

Kavimandan

Gokhale

2009

Lecture Notes in Computer Science

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Abstract. The quality of a software architecture for component 1 -based distributed systems is defined not just by its source code but also by other systemic artifacts, such as the assembly, deployment, and configuration of the application components and their component middleware. In the context of distributed, real-time, and embedded (DRE) component-based systems, bin packing algorithms and schedulability analysis have been used to make deployment and configuration decisions. However, these algorithms make only coarse-grained node assignments but do not indicate how components are allocated to different middleware containers on the node, which are known to impact runtime system performance and resource consumption. This paper presents a model transformation-based algorithm that combines user-specified quality of service (QoS) requirements with the node assignments to provide a finer level of granularity and precision in the deployment and configuration decisions. A beneficial side effect of our work lies in how these decisions can be leveraged by additional backend performance optimization techniques. We evaluate our approach and compare it against the existing state-of-the-art in the context of a representative DRE system.

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Section: Discussionmentioning

confidence: 99%

Applying Model Transformations to Optimizing Real-Time QoS Configurations in DRE Systems

Kavimandan

Gokhale

2009

Lecture Notes in Computer Science

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“…The measurement probes can be turned on and off at runtime. Diaconescu et al (2004) introduce an approach where a transparent proxy layer for data collection is automatically generated at deployment time. The JBoss Application Server, for instance, enables the transparent aspect-oriented addition of functionality.…”

Section: 6) Performance Monitoringmentioning

confidence: 99%

Quality-Aware Model-Driven Service Engineering

Pahl

Bošković

Barrett

et al. 2009

Model-Driven Software Development

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Abstract. Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services.Keywords. Service-oriented architecture, model-driven development, software product quality, architectural modelling, patterns, empirical performance evaluation. 1) IntroductionWith software services becoming a strategic capability for the software sector, a service engineering discipline needs to address service development problems based on suitably flexible modelling and composition support. An increasing need for flexibility in this area is caused by changing user requirements, evolving services, and varying deployment contexts. Software services are application that are provided 'as-is' at certain locations in order to be integrated into existing applications or composed to larger systems. Essential in this process are abstract descriptions or models of the service functionality and other service characteristics. This makes model-driven software development both a highly suitable, but actually also necessary framework to adequately develop service-based software systems. Composition and integration-oriented modelling has already been successfully utilised for model-driven services development. The high complexity of modern software makes its development costly and error-prone. Model-driven development (MDD) is an approach that deals with software complexity by making software models primary artefacts of the software development process. MDD utilises two aspects of models. Firstly, in various engineering disciplines, predictions about a software system can be made based on a model. Secondly, even complete implementations for different platforms and languages can be generated from models.The aim of this chapter is to address quality aspects of model-driven service engineering. We address two specific facets of quality assurance for model-driven software development: the model-driven design and development of high-quality software and the identification of quality aspects in model-driven development. Some specific aspects that we discuss in the context of quality aspects in model-d...

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“…Recent work in automatic inference of the behavior of complex applications relies on collecting fine-grained (component-level) observations and extracting interesting patterns from them [15,21], whereas recent progress in applying automated management techniques [20,31] assume a predictable performance cost for triggering management mechanisms such as recovering or activating a node. We combine similar techniques in the context of our three-tier J2EE prototype system.…”

Section: Autonomic Computingmentioning

confidence: 99%

Autonomous recovery in componentized Internet applications

et al. 2006

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In this paper we show how to reduce downtime of J2EE applications by rapidly and automatically recovering from transient and intermittent software failures, without requiring application modifications. Our prototype combines three applicationagnostic techniques: macroanalysis for fault detection and localization, microrebooting for rapid recovery, and external management of recovery actions. The individual techniques are autonomous and work across a wide range of componentized Internet applications, making them well-suited to the rapidly changing software of Internet services.The proposed framework has been integrated with JBoss, an open-source J2EE application server. Our prototype provides an execution platform that can automatically recover J2EE applications within seconds of the manifestation of a fault. Our system can provide a subset of a system's active end users with the illusion of continuous uptime, in spite of failures occurring behind the scenes, even when there is no functional redundancy in the system.

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Automatic performance management in component based software systems

Abstract: Abstract

Cited by 30 publications

References 11 publications

Applying Model Transformations to Optimizing Real-Time QoS Configurations in DRE Systems

Applying Model Transformations to Optimizing Real-Time QoS Configurations in DRE Systems

Quality-Aware Model-Driven Service Engineering

Autonomous recovery in componentized Internet applications

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